1. Field of the Invention
The invention is related to the field of Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) apparatus and methods. More particularly, the invention relates to apparatus and methods for determining a known component from a mixture of unknown components. More specifically, the invention relates to methods and apparatus for using NMR for precise and quantitative determination of material composition. In one application methods and apparatus according to the invention relate to using NMR for rapid, quantitative in-vivo determination of tissue properties, such as Fat-to-Lean ratio.
2. Background Art
The description of the invention and its background are explained herein in the context of Fat-to-Lean ratio determination. It is to be explicitly understood, however, that the invention is not limited to analysis and monitoring of Fat-to-Lean ratio. For example, Fat-to-Lean-to-Bone ratio may also be determined using methods and apparatus according to the invention. Fat composition (different fatty acids), lean composition (water, protein, and glycogen), and bone composition (mineral, collagen, and water) may also be determined using methods and apparatus according to the invention.
In human health monitoring and treatment, the level of total body mass that is derived from adipose mass is the variable that has been determined empirically to be most closely associated with risk for pathology. Advanced models of body composition and newer technologies that precisely and accurately calculate adipose mass may eventually replace simple anthropometric methods such as body weight, height, waist circumference, skin fold thickness, etc. in determining likelihood of pathology.
Body Mass Index (BM) is defined as body weight (kg)/height2 (m2). Although BMI is a reasonable marker of energy balance for individuals, it is very rough marker of adiposity across populations.
Hydrostatic weighing or Under Water Weighing (UWW) has been the most preferred technique for human whole body composition analysis for several decades. However, due to several practical inconveniences and questionable underlying assumption its usage is limited. UWW assess whole body fat content expressed as a percentage of body weight. See, for example, U.S. Pat. No. 4,873,866 to Fairbanks.
UWW based on a two-component (2C) body composition model assumes specific densities 0.9 and 1.1 g/cm3 for Fat Mass (FM) and Fat-Free Mass (FFM) respectively. UWW further assumes that these densities are constant within different individuals or populations. Whole body densities have been determined to vary in a range between 1.08 g/cm3 (very lean) and 1.00 g/cm3 (severely obese).
Other UWW techniques are based on four-component (4C) or three-component (3C) body composition models. 4C and 3C models additionally use assumptions that FFM is composed of constant proportions of water (73.2%), minerals (6.8%), and protein (19.5%) each having a specific density assumed to be constant at body temperature. Precise measurement of Total Body Water (TBW) and Bone Mineral Content (BMC) are required to use 4C and 3C models because of the potential for additional error in the final results for FM that is related to TBW and BMC measurements. In certain human population groups, such as children, the elderly, African-Americans, or sick patients, 4C or 3C methods may provide more accurate estimates of FM than the 2C method.
UWW is not practical for accurate measurements in individuals having cardiovascular or pulmonary disorders, elderly, young children, and very obese subjects. Substantial errors may occur due to body movement and the buoyant effects of air in the gastrointestinal tract and lungs. The simultaneous measurement of residual lung volume and underwater weight may be preferred because it controls for the effects of the increased pressure of water on the thorax during immersion. Inaccurate measurements of air in the lungs can be a major source of error when estimating body density from underwater weighing. However, UWW may be the only practical method of measuring body fat in very obese subjects who cannot be evaluated by other methods.
U.S. Pat. No. 4,144,763 to Vogelman and U.S. Pat. No. 5,105,825 to Dempster disclose plethysmography apparatuses and methods. Plethysmography is a more convenient way for measuring body adiposity as compared to UWW. Measurement of body density by plethysmography allows for a high degree of precision in volume measurement, but inconsistencies in body density, the necessity for lung volume correction, variation in skeletal mass, and degree of hydration are not accounted for by plethysmography methods.
U.S. Pat. No. 6,393,317 to Fukuda et al. and U.S. Pat. No. 5,415,176 to Sato et al. disclose two examples of widely used techniques for fat assessment based on body bioelectrical impedance. A method for fat assessment based on body electrical conductivity is described by Unangst E. T., Jr., and Merkley L. A. in, The effects of lipid location on non-invasive estimates of body composition using EM-SCAN technology, J. Exp. Biol., 2002:205 (Pt. 19) pp. 3101-3105.
None of the foregoing methods of body composition analysis have been broadly implemented, largely because of inaccuracy and poor specificity of the results. Measurement of body composition of experimental animals by plethysmography, hydrostatic weighing (UWW), bioelectrical impedance, and electrical conductivity has not proven to be practical.
In order to provide a more precise quantitative measure of whole body composition in animals, the Dual Energy X-ray Absorptiometry (DEXA) technique is more widely used than the foregoing techniques. U.S. Pat. No. 6,233,473 to Shepherd et al. discloses a method of body composition analysis using a dual-energy, fan-shaped distribution of X-rays, and detector signal processing that corrects for mass magnification and other effects due to the geometry of the measurement system. In the method disclosed in the '473 patent, the thickness of the attenuating material along respective ray paths is obtained by using a four-dimensional look-up table derived experimentally from step-wedge measurements, and another look-up table and interpolation between table entries are used to convert projected mass to true mass.
DEXA precision differs with the instrument type, the particular animal species being evaluated, the software and the actual methods that are used. The basic physical principle of DEXA is associated with attenuation of X-rays transmitted through an object. The degree of attenuation (attenuation coefficient) depends on the object's thickness, density, and chemical composition as well as the initial energy of the X-ray photons. At low initial photon energies (less than about 0.8 million electron volts), photon attenuation is non-linear, and is governed by the photoelectric effect and by Compton scattering. If the object under evaluation is composed of two or more homogeneous materials, then the composite attenuation coefficient may be approximated by a weighted sum of the individual attenuation coefficients, each weighted for its fractional contribution to the total mass.
The attenuation of X-rays through lean human body tissue and fat tissue is slightly different, but is substantially different for bone tissue, primarily because of their differences in density and chemical composition. DEXA does not provide three independent measurements, even though three body composition values: bone; lean; and fat tissue fractional amounts are reported. With increasing initial photon energy, the differences in the attenuation properties for these three types of body tissue decrease.
The following is summary of a DEXA technique for whole body composition analysis of laboratory mice. First, a record is made of the attenuation of X-rays at both initial photon energy values in air. Then the pixel size, scanning speed and beam size are selected. A scan of the object (mouse) is then made. The detected X-ray photon amplitudes and count rates are corrected for detector dead time loss, spill-over from one energy window to another, and for beam hardening. From two equations (two photon energy levels) the amount of soft tissue and bone mineral is then determined.
Soft tissue in the non-bone pixels is separated into fat and lean mass by means of a calibration that translates attenuation coefficients into fat fractions. Corrections are made for tissue thickness variation. The fat content of the soft tissue layer overlying, underlying and/or inside bone is estimated based on predetermined relationships between fat-to-lean ratio of pure soft tissue surrounding bone.
The main advantage of DEXA is the ability to analyze individual regions within an entire body. DEXA as a method for analyzing whole body composition may be subject to the following limitations. First is the assumption that the composition of the soft tissue layer overlying bone has the same Fat-to-Lean ratio, or the ratio is related in a predetermined way to the Fat-to-Lean ratio of other non-bone tissues. For a whole body scan, about 40% of the pixels are typically classified as containing bone. Next, thicker tissue regions remove more low energy photons from the radiation beam as compared to thinner regions, this effect being known as “beam hardening.” Further, DEXA assumes homogeneous hydration of lean tissues.
In the field of in-vivo analysis of body composition parameters there have been numerous attempts to use Nuclear Magnetic Resonance (NMR) methods and apparatus. Briefly, these techniques and their limitations are as follows.
I. Magnetic Resonance Spectroscopy (MRS). The MRS method used to quantify fat content in a body is based on recording a 1H (proton) spectrum in-vivo. An example of using a standard MRS apparatus for such analysis is described by Mystkowski et al. in, Validation of whole-body magnetic resonance spectroscopy as a tool to assess murine body composition”, Int. J. of Obesity, 2000:24, pp. 719-724. A drawback to the technique disclosed in the Mystkowski et al. paper is the fact that many human tissue types contain a variety of lipids which yield 1H spectral peaks within a very narrow chemical shift range. In addition, MRS requires very high homogeneity and strength of the static magnetic field, due to the required high spectral resolution of chemical shifts, making MRS equipment that would be used for whole body composition analysis extremely expensive.
II. Magnetic Resonance Imaging (MRI). A MRI method for body composition analysis is described by Ross et al. in, Quantification of adipose tissue by MRI: relationship with anthropometric variables, J. Appl. Physiol. 1992:72(2) pp. 787-795, and in U.S. Pat. Nos. 5,225,781; 5,594,336; 6,147,492; and 5,644,232.
III. NMR Relaxometry. NMR relaxometry methods known in the art avoid the necessity for complicated and expensive equipment. NMR relaxometry methods known in the art, however, have several limitations, such as with respect to accuracy and precision. Kamman et al., Multi-exponential relaxation analysis with MR imaging and NMR spectroscopy using fat-water systems, Magn. Reson. Imaging 1987:5(5) pp. 381-392 describes a NMR relaxometry method for body composition analysis. Despite extensive research and development into methods of whole body composition analysis, there is still a need for reliable, accurate, precise, and specific non-invasive methods for acquiring information relating to body fat mass, lean mass, total water content, etc.
Furthermore, methods known in the art for composition analysis from NMR measurements, such as Carr-Purcell-Meiboom-Gill sequence spin echo amplitude measurements, typically use multicomponent exponential decay decomposition to determine the fractional amounts of selected components in the body or other material being analyzed. Such methods are not particularly suitable for use with some types of NMR apparatus for body composition analysis because of the relatively low radio frequency used for the RF magnetic field (associated with the relatively low amplitude static magnetic field). There are only small differences in the amplitude decay of spin echo measurements for the various components of a body being analyzed, and as a result, it has proven necessary to develop different techniques for analyzing body composition from NMR measurements.